Carnegie Mellon University
Browse
sjia1_Tepper_2022.pdf (4.1 MB)

Learning and Earning Under Noise and Uncertainty

Download (4.1 MB)
thesis
posted on 2022-07-11, 20:57 authored by Su JiaSu Jia

Sequential decision-making under uncertainty is central to a range of operations and marketing problems. In the face of an unknown environment, decision-maker needs to strike a balance between learning the known environment (“learning”) and selecting nearly optimal decisions (“earning”). For instance, consider pricing a new product. If the retailer had full information about the demand at every price level, then she could determine the revenue-maximizing price for the good. However, such information about the demand curve is typically not available in practice, so the seller needs to experiment with different prices to gain information about the demand curve, and then exploit this information to offer a near-optimal selling price.

History

Date

2022-05-12

Degree Type

  • Dissertation

Department

  • Tepper School of Business

Degree Name

  • Doctor of Philosophy (PhD)

Advisor(s)

R. Ravi Andrew Li

Usage metrics

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC